FX Algo Systems

We develop: 1) High-frequency arbitrage systems for interbank pricing gaps, 2) Volatility harvesting models for news events, 3) Machine-learning trend classifiers, 4) Carry trade optimizers with volatility filters, and 5) Liquidity-provision algorithms capturing bid-ask spreads. All strategies include multi-currency calibration.

Our backtesting framework features: 1) Tick-level historical data (10+ years depth), 2) Multi-broker slippage modeling, 3) Latency simulations matching your execution environment, 4) Rollover cost incorporation, and 5) Monte Carlo robustness testing. Reports include drawdown stress tests under extreme volatility regimes.

Yes. Our adaptive execution engines feature: 1) Pre-news volatility filters, 2) Liquidity-seeking order routing, 3) Spread-widening detection systems, and 4) Time-sliced VWAP execution during events. These reduce NFP/Central Bank slippage by 40-75% in live testing.

We provide solutions for: 1) Python (full quant libraries), 2) MQL4/5 (ready-to-deploy MT4/MT5 EAs), 3) C# for institutional platforms, and 4) No-code builders with drag-and-drop strategy designers. All include API documentation and optimization guides.

We prevent curve-fitting through: 1) Walk-forward optimization with rolling out-of-sample periods, 2) Parameter stability zones identification, 3) Regime-shift detection systems, and 4) P&L consistency scoring across market environments. Strategies must maintain Sharpe >1.2 across 5 volatility regimes.

Yes. Our multi-asset framework features: 1) Cross-pair correlation constraints, 2) Volatility-normalized position sizing, 3) Liquidity-aware execution sequencing, and 4) Centralized risk exposure monitoring. Portfolio-level backtesting shows how strategies interact across 28 major currency pairs.